Engineering and manufacturing industries

Knowledge based systems which have information in linguistic form are important in the construction of expert systems. Fuzzy sets and approximate reasoning provide methods of representing and reasoning with imprecise information. An algorithmic approach for developing a knowledge tree and evaluating information requests is presented. Possibility distributions are used to represent information in a linguistic value. The focus is on determining the value of a variable from a knowledge base.

Opposites and Measures of Extremism in Concepts and Constructs

Article Abstract:

Two primary forms of opposites, negation and antonym, are discussed in terms of representation by fuzzy sets. The fuzzy set framework provides for both quantification of and distinguishment between the opposites. A measure of extremism of a class of elements is presented. It provides a means of analysing usefulness with respect to a concept and its negation or its antonym.

Quantified Propositions in a Linguistic Logic

Article Abstract:

Quantifiers are use to make summary statements about the properties of a class of objects. Two methods are presented for interpreting quantifiers in binary logic. Fuzzy set theory is used to extend the interpretations to linguistic quantifiers. Various methods of measuring the cardinality of fuzzy sets are discussed. The concept of fuzzy cardinality is presented.